How to improve operational efficiency in your institution

The need to drive effective strategies through data has become a principal challenge across the higher education system.

Yet, while efficiencies in data and workflows are key to success, demonstrating research impact and sound decision-making are also key for institutions, adding extra layers of complexity to how finite resources are distributed.

Funding is increasingly competitive, with the allocation of resources becoming further exacerbated by the level of complexity and scarcity. Academic leaders globally are united in their institutional priorities; and while a key focus area is their desire to secure funding, another is their proactive drive to leverage data, knowledge and collaboration to their advantage.

Industry trends in research funding

Securing finance for research remains an undeniable priority for academic leaders and funders. 84% rank this as a top challenge in an industry-leading Ipsos and Elsevier study opens in new tab/window, with two-thirds (66%) predicting this challenge will increase over the next five years – preceded only by research excellence and facilities for research (Fig. 1).

Funding forms the foundation and springboard for research outputs and education. However, in July 2024 opens in new tab/window, Times Higher Education (THE) reported an increase in UK universities’ research funding deficit to £3.9 billion. In the US, the rate of inflation impedes government funding pools, where there has been a notable trend in the reduction of state appropriation per FTE student, at an average drop of $1,500 per student opens in new tab/window between 2008 and 2020. Net tuition also fell by 3.3% per student opens in new tab/window in 2023, the result being that universities are continually challenged to stretch funding resources further than their essential areas. In spite of this trend [funding declining], according to data from the OECD and UNESCO, the number of researchers worldwide has been growing at a pace of around 3-5% year on year. opens in new tab/window

Once secured, funding often comes with strings attached, with pressure to ensure that you are “hitting the mark with research and spending money appropriately,” said one Executive Director of Research and Project Administration at a US institution. Therefore, the decisions that surround the “why” “where” and “how” to spend your budget become increasingly complex, with the inevitable prioritization that ensues (Fig. 2).

Strategies for research funding

There is an administrative burden that accompanies the workflow of successful funding applications, with a core challenge being: “how to find and align your most capable researcher in terms of their specific skill set, area of expertise with those funding agencies,” said a Senior Director at a leading US academic institution.

There is also a significant amount of data and research information that drives an institution’s successful funding application, and the continued, related workflows. Included in this is the know-how for targeting the best opportunities, matching funder programs to your research interests and keeping faculty abreast of relevant opportunities, so that they can contribute selectively, without being bombarded.

Across the world, the opinions of academic leaders are clearly united: institutional priorities are numerous, and vast, and the level of preparedness is collectively low regarding their ability to address ongoing strategic goals (Fig. 1).

The agility provided in using data to your advantage and creating effective workflows can bring structure to these complex, strategic goals – as aptly stated by one US academic leader: “There are data challenges affecting everyone. What if we could make things go faster? […]” underpinning a clear desire for momentum.

Research excellence – How to collaborate more effectively

In recent years, institutions have been working together more closely across teaching and research, maximizing resources and funding, and accelerating impact, by exploring co-creation and collaboration models. Some examples include:

University-industry collaboration (US)

In the US, the Directorate for Technology, Innovation and Partnerships (TIP) – the first new National Science Foundation (NSF)directorate in 30 years – is launching an investments pilot opens in new tab/window and embarking on a mission to “create growth and jobs in the US through boosting ‘use-inspired’ R&D.” opens in new tab/window The TIP doubled its budget to $880 million last year, with innovation surfaced by the initiation of new collaborative partnerships, or “industry clusters opens in new tab/window” with other researchers globally.

University-industry collaboration (UK)

In the UK, Advanced Oxford, an Oxfordshire-based collaboration with Elsevier, developed an innovation dashboard opens in new tab/window that supports the local ecosystem in measuring the combined impact of the region, facilitating research strategy, evaluation and policy. The dashboard tracks data on how Oxfordshire’s science and technology business community impacts economic activity in the UK – effectively, combining the output data of multiple entities for use by policymakers, planners, investors, companies and the universities.

University-industry collaboration (APAC)

In Japan, Elsevier’s Pure has supported similar co-collaboration operations through the MIRAI-DX project opens in new tab/window. As part of this initiative, research administrators from 40+ Japanese institutions have combined their data into a sole interface, allowing them to leverage their combined networks and outputs towards securing larger funding opportunities in SDG- and Covid-19- driven research. By combining their research information with KAKEN’s funding data research fields, they can easily surface the most targeted information for each application (Fig. 3). With similar research goals in mind, and the shared problem of decreasing funding success rates in a highly competitive market, the consortium’s active promotion of problem-solving joint research through the portal has opened new revenue streams for multiple institutions (Fig. 3).

For institutions globally, this serves as another example underlining the link between collaboration and creating innovative funding opportunities. What is clear is that universities go faster when they go – or collaborate well – together.

Accelerating the impact of your organisation

The demonstration of real-world impact is being propelled up the leadership agenda. In a new study examining academic evaluation, 79% of academic leaders, researchers and funders were cited as supporting a new approach for research assessment.

There is a growing pressure to demonstrate the broader societal and economic impact of research beyond traditional bibliometrics. The overreliance on quantitative proxy measures leaves space for showing an institution’s wider reach of its scholarly outputs – a key driver in facilitating fortune-changing funding opportunities and attractive collaborative partnerships.

"There will be a redefinition of the core task of universities. That is something which we see happening now in a lot of countries, universities asking themselves what is our goal in society and for society?" Academic Leader, Europe, Middle East & Africa Source: View from the Top, Elsevier & IPSOS, 2024

Actively proving success rates in venture capital flows, patents, start-ups, jobs created and influence on local and larger-range policy are all crucial factors in the allocation of public investment, and, therefore, further funding validation. One academic leader noted the validity of these metrics in demonstrating the more immediate impact of research versus existing measures:

Demonstrating impact with the REF

In the UK, the cost of running the REF has meant that the British government is closely monitoring cost within the system with a desire to drive efficiencies, meaning that the measurability of research impact has adopted a new and greater significance. As stated by Sarah Main, Vice President Academic and Government Relations UK, Elsevier: “The idea that universities spend huge amounts of money running the research excellence framework is not popular.” Therefore, institutions will likely feel a pressure to prepare for the REF submission in an efficient way, and reduced costs – and there are financial benefits for those who can execute this well.

Key findings | Best practices on impact

Talent management – How to showcase your institution’s most valued asset

Without question, funding constraints limit an institution’s talent, people management and hiring strategies. 93% of academic leaders globally stated that they need more funding to attract and retain the right talent, with just 11% stating they feel well prepared to offer competitive compensation and benefits to staff.

Workflows and workloads in academia

There is vast data to show that faculty workloads are increasing. Recent research shows that, in the US, academics are working more than they are paid to do, equating to 2 unpaid days (50.4 FTE hours) per week. While there is more focus needed in this area, significant progress is being made:

Workloads are unrelenting across academia, with 66% of faculty reporting burnout opens in new tab/window – attributing it to “unremitting workload of 70+ hrs per week, poor leadership, top-heavy administration and devaluation of faculty.”

Finding the space to showcase their institution’s most valued asset – its key to competitive advantage in academic excellence – is top of mind for many leaders. As well as the significant challenges surrounding staff engagement, hiring processes, ensuring work-life balance and reporting on high-value faculty work feeding the institutional strategy (Fig. 4).

Best practice strategies for retaining faculty

In light of these challenges, what are the key strategies for success to retain your faculty? Best practices noted by some institutions include: mentoring and guidance programs from senior faculty, conducting exit interviews to understand why faculty leave, leadership opportunities and providing supportive communities at the institution (Fig. 5).

Reimaging the tenure and promotion process

The workflows surrounding hiring processes further complicate strategic talent sourcing and management. A lack of standardized data, processes and templates can hinder efficiencies in tenure and promotion processes. 73% of tenured professors moved up their retirement date in last year, according to a report from the Chronicle of Higher Education opens in new tab/window. There is also a limited guarantee that disorganized data and workflows will lead to equitable hiring and tenure and promotion processes. However, many examples exist of how leveraging data in aid of efficiency has supported faculty and senior leadership in making the right hiring decisions and retaining talent.

On the topic of the standardization of tenure and promotion processes, Courtney Bryant, Office of the Vice Provost for Faculty, Carnegie Mellon University stated: “It’s hard to read cases when they’re not standardized, it’s hard to ensure that you have a good process and the right materials, so standardization is key to a smooth process and fair process.” The structure and focus that data provides for effective planning also allows for more focused, precision committee work, enhancing productivity for senior-level staff.

If datasets, systems and processes are fully structured to support agility and high performance, and in the most effective way to benefit faculty and staff, this frees up the university’s brightest minds to make a more dynamic, deeper impact in research and education. Unstructured data and processes around scholarly activities can lead to hiring missteps, missed promotion chances, or the most relevant research work not being surfaced at the right time.

Source: White Paper: Faculty Diversity in Review, Promotion, and Tenure opens in new tab/window, Interfolio, 2024

D. Harley, S.K. Acord, S. Earl-Novell, S. Lawrence, C.J. King, “Assessing the Future Landscape of Scholarly Communication: An Exploration of Faculty Values and Needs in Seven Disciplines,” Center for Studies in Higher Education, 2020

Promoting equality, diversity and inclusion in academia

On diversity in the promotion and review process, Sian Smith, Assistant Director, Faculty HR Research and Faculty Office, London Business School states: “We think really carefully about that to ensure that when the school is conducting a review it’s made up of a diverse range of people that represent who they’re then going to be reviewing. They’re some of the things that we might not have thought about 5 or 10 years ago.” Sian also mentions that, in the UK, universities are required to publish their gender pay gap data, noting that this sharp focus provokes some “difficult” but “really important” conversations.

Source: White Paper: Faculty Diversity in Review, Promotion, and Tenure opens in new tab/window, Interfolio, 2024

Talent and the “4^th generation university”

“Talent” is not limited to university faculty. Student engagement takes centre stage in the Eindhoven University of Technology (TU/e) and Elsevier’s 2024 report, “Towards the 4th generation university opens in new tab/window”, which depicts universities as a “gateway for talent,” loaded with potential to transform the innovation and technological breakthroughs of the region. At Eindhoven, almost half of the alumni (46.7%) remain within 75km of the university following their studies and 75.1% remain within the Netherlands. A “4^th generation university” is touted as a new model that “gives rise to new units within universities, such as innovation spaces, and to multi-stakeholder partnerships with a specific focus on challenges or technologies.” (Fig. 6)

In considering the state of the market in higher education, there is a clear consensus for change among leading academic institutions. All the data and know-how would suggest that talent is king; as a key driver for the success of the university, they are also drivers for thought, the primary opinion leaders for research excellence, as well as those leading and shaping the structure of student programs for the future cohorts.

As universities look to the “4^th generation” model for institutions, many are considering varying frameworks for how data is organized, how faculty is secured and developed and ultimately, the forever changing university experience. Overall, in accelerating research impact and excellence, going faster appears just as critical as going faster, together, as new and innovative partnerships emerge.